Triple
T35181194
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Younger |
E1015852
|
entity |
| Predicate | hasLifeInsurancePolicy |
P197644
|
FINISHED |
| Object | $10,000 |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: $10,000 | Statement: [Mr. Younger, hasLifeInsurancePolicy, $10,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLifeInsurancePolicy Context triple: [Mr. Younger, hasLifeInsurancePolicy, $10,000]
-
A.
hasInsurancePolicyOnVictim
Indicates that an entity holds an insurance policy that covers or is taken out on the victim.
-
B.
isOnPolicy
Indicates that an action, configuration, or behavior complies with and adheres to a specified policy or set of rules.
-
C.
insuranceType
Indicates the specific category or kind of insurance coverage associated with an entity or relationship.
-
D.
hasEmergencyCoverageFor
Indicates that one entity provides or is assigned emergency-related protection, service, or support for another entity.
-
E.
insurance
Indicates a relationship where one party provides financial protection or coverage to another against specified risks or losses, typically in exchange for payment.
- F. None of above. chosen
Provenance (4 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f76ddcc108819097f96853b7ed9ef4 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fe9fb9735c8190a360b556c9d00b3f |
completed | May 9, 2026, 2:45 a.m. |
| PD | Predicate disambiguation | batch_69fe9eaa88008190a9b2a469dc685002 |
completed | May 9, 2026, 2:40 a.m. |
| PDg | Predicate description generation | batch_69fe9fb88db08190a8f4af350633330e |
completed | May 9, 2026, 2:45 a.m. |
Created at: May 3, 2026, 4:02 p.m.